Quantum Computing

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Quantum computing uses quantum mechanical effects to perform calculations that are far beyond the capabilities of conventional supercomputers. Thus, it holds the potential to efficiently deal with problems in the future that are unsolvable today. With the two focal points quantum machine learning and quantum optimization, the department studies industry-relevant applications and methods in order to support the transfer on a broad industrial scale at an early stage. The focus is on the new and further development of quantum algorithms taking in particular the current progress in hardware into account.

As part of the Fraunhofer “Quantum Computing” competence network, Fraunhofer IPA has exclusive access to the IBM Q System One, Europe's first commercial quantum computer, which went into operation in Ehningen near Stuttgart in 2021.



Automated machine learning (AutoML) enables low-threshold access to AI solutions. The “AutoQML” project extends this approach with quantum computing-based methods so that it can be transferred to industry at an early stage.



In the SEQUOIA project, software for industrial hybrid quantum applications and algorithms is being engineered. In the project, new methods, tools, and procedures for quantum computing are researched, developed, and tested with a view to making them suitable for industrial use in the future.



The “Degrad-EL3-Q” project focuses on finding ways to use quantum computers in order to analyze the lifetime of electrolyzers. It forms part of the lead project “H2Giga”, in which the serial production of electrolyzers is being developed.



AQUAS aims to make the catalytic processes of electrolytic materials accessible through quantum simulations. Fraunhofer IPA is conducting research on quantum-based AI methods to complement these simulations.